Relationship between semen parameters and spontaneous pregnancy

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1 Relationship between semen parameters and spontaneous pregnancy Sreebala Sripada, M.R.C.O.G., a John Townend, Ph.D., b Doris Campbell, M.D., c Linda Murdoch, B.A., d Eileen Mathers, M.Sc., e and Siladitya Bhattacharya, M.D., F.R.C.O.G. c a Aberdeen Maternity Hospital, Aberdeen, United Kingdom; b Medical Research Council, Banjul, Gambia; c Department of Obstetrics and Gynecology, University of Aberdeen, Aberdeen Maternity Hospital, Aberdeen, United Kingdom; d Dugald Baird Centre, Aberdeen Maternity Hospital, Aberdeen, United Kingdom; and e Andrology Laboratory, National Health Service Grampian, Aberdeen Maternity Hospital, Aberdeen, United Kingdom Objective: To explore the association between semen parameters and spontaneous pregnancy. Design: Case control study. Setting: Aberdeen Fertility Centre, Aberdeen, Scotland. Patient(s): A total of 1,426 untreated couples attending a subfertility clinic with no evidence of azoospermia, anovulation, or tubal disease were observed for 180 weeks. Cases were couples who achieved conception spontaneously within the follow-up period; controls were those who did not. Intervention(s): None. Main Outcome Measure(s): Sperm density, sperm motility, and sperm morphology. Result(s): In women who achieved spontaneous conception (n ¼ 488) the mean (SD) age was 30.6 (4.8) years and median (interquartile range) parity was 1 (0 1), compared with 32.0 (5.4) years and 1 (0 1) in those who did not (n ¼ 938). The median (interquartile range) duration of infertility was 24 (17 36) and 18 (14 24) months in nonpregnant and pregnant couples, respectively. After adjusting for male and female age, parity, year of first visit, and duration of infertility, sperm motility and normal morphology were significantly associated with spontaneous pregnancy, whereas sperm density was not. For motility, the area under the receiver operating characteristic curve was (95% confidence interval ). For morphology, the area under the receiver operating characteristic curve was (95% confidence interval ). Conclusion(s): In subfertile couples, sperm motility and morphology have limited predictive value for spontaneous conception. (Fertil Steril Ò 2010;94: Ó2010 by American Society for Reproductive Medicine.) Key Words: Semen parameters, semen analysis, spontaneous pregnancy Conventional semen analysis (comprising assessment of density, motility, and normal morphology) continues to be a routine component of baseline fertility investigations. There are uncertainties about normal values for semen density and motility and unresolved questions about the predictive value of a routine semen analysis as a diagnostic test. Recent evidence has questioned the clinical value of the existing World Health Organization (WHO) criteria for basic semen analysis in the prediction of fecundity (1, 2). This is reflected in the WHO recommendation suggesting that laboratories need to evaluate their own reference range for each sperm parameter. Although objective measures of progressive sperm motility and detailed morphology, including acrosomal status, are significantly correlated with fertilization in vitro (3), data on their association with spontaneous conception are limited. This uncertainty can lead to inaccurate diagnosis, Received January 28, 2009; revised February 24, 2009; accepted February 25, 2009; published online April 9, S.S. has nothing to disclose. J.T. has nothing to disclose. D.C. has nothing to disclose. L.M. has nothing to disclose. E.M. has nothing to disclose. S.B. has nothing to disclose. This study was funded by the University of Aberdeen. Reprint requests: Sreebala Sripada, M.R.C.O.G., Aberdeen Maternity Hospital, Cornhill Road, Aberdeen AB25 2ZD, United Kingdom (FAX: ); ogy302@abdn.ac.uk). inappropriate treatment, and unnecessary anxiety. There is therefore a need to determine which of the commonly used sperm parameters offer the best prognostic value in terms of predicting pregnancy leading to live birth. The aim of this study was to explore the association between semen parameters and spontaneous pregnancy among subfertile couples. Aberdeen provides an optimal setting for exploring a clinical question of this nature because of its relatively stable population with low emigration rates (4, 5) and comprehensive, population-based data captured in two large, local databases (the Aberdeen Maternity and Neonatal Databank [AMND] and the Aberdeen Fertility Clinic Database [AFCD]). The AMND, set up in 1950, records all obstetricand fertility-related gynecologic events for women resident in the Aberdeen City District (6). The AFCD contains detailed records of all couples seen in the Aberdeen Fertility Clinic (AFC) since The AFC is the only specialized fertility clinic in the Grampian Region of Scotland, and all couples with fertility problems in the region are referred to it by their general practitioners. Investigation and management of couples presenting with infertility is based on a standard protocol in terms of investigations and diagnosis, and all details are entered prospectively into a dedicated database. Both databases have complete coverage of the eligible population and possess stringent quality control measures to 624 Fertility and Sterility â Vol. 94, No. 2, July /$36.00 Copyright ª2010 American Society for Reproductive Medicine, Published by Elsevier Inc. doi: /j.fertnstert

2 ensure validity and reliability of data. Data in the AFCD on mode of conception (treatment related or spontaneous) were supplemented by a case note review to ensure accuracy and completeness. Record linkage between the two allows complete reproductive histories to be obtained. MATERIALS AND METHODS We identified couples residing in Aberdeen City District (according to their postal codes) presenting to the AFC with infertility. Because all pregnancies in this population are recorded in the AMND, restriction of study patients to residents of Aberdeen City District ensured that all reproductive outcomes in women in the area would be available in the AMND. Moreover, the emigration rate for this postal-code area is low (7, 8), thus ensuring that the numbers of women who move away and deliver elsewhere are likely to be very small. Fertility clinic records of women were then matched with records held in the AMND to ascertain pregnancy outcomes, including live births, stillbirths, ectopic pregnancies, and miscarriages. Because all pregnancies, both deliveries and unsuccessful pregnancies, in women living in Aberdeen City District are recorded in the AMND, women attending the fertility clinic who had no AMND records were assumed not to have had a pregnancy. Inclusion Criteria All couples resident in Aberdeen City District and referred to the AFC from 1994 to 2003 (n ¼ 5,077) were included in the study (Fig. 1). Exclusion Criteria Couples with no semen analysis report or history, findings suggestive of azoospermia, fallopian tube blockage, or anovulation, a history of vasectomy and/or female sterilization, as well as couples who underwent any form of fertility treatment or used donated gametes were excluded from analysis. Data Collection and Linkage Clinical and laboratory data were collected from all couples attending the AFC. Maternity-related data in all women in the region are routinely collected and recorded in the AMND. Stringent and consistent coding criteria, which are essential for studies of secular change, have been used for the coding of gestational length, birth weight, and pregnancy complications, as well as the classification of perinatal events within the AMND. After approval of the Caldicott guardians of the Fertility and Maternity Databases, data from the AFCD were linked to the AMND by the data management team and all pregnancy-related outcomes identified. After linkage, data were anonymized by removal of identifiers before being made available to the researchers. We were advised by the North of Scotland Research Ethics Committee that a formal ethics application was not required because all analyses were performed on an anonymized dataset. Reattendance Only records from the first attendance at the fertility clinic were included for couples who changed partners and reattended the clinic and for couples who reattended the clinic for a second conception. Semen Analysis The northeast of Scotland is served by a single andrology laboratory. All samples in the study were analyzed according to standard laboratory instructions by a computer-assisted method. The first sample produced by each man was considered. FIGURE 1 Flow diagram of couples selected for analysis. Total number of couples attending Aberdeen fertility centre and resident in Aberdeen city district from = 5077 Azoospermia and missing sperm analysis = 1500 Tubal factor = 867, Sterilisation = 20 Vasectomy or reversal = 101 Ovulation disorders = 720 Sripada. Semen parameters and spontaneous pregnancy. Fertil Steril Donor gamete = 2 Pregnant by treatment = 653 Number excluded 3863 Number matched with AMND = 1426 Spontaneous conceptions = 488 Non-pregnant = 938 Fertility and Sterility â 625

3 Men were instructed to abstain from ejaculation for 3 7 days before providing a sample by masturbation into a sterile plastic container. The sample was allowed to liquefy at 37 C for an initial period of minutes, and all analyses were performed within 90 minutes of ejaculation. The volume of the ejaculate was determined by aspirating the liquefied sample into a graduated disposable pipette. To determine the concentration of sperm (10 6 /ml) and sperm motility, a 10-mL drop of the semen sample was placed on a commercially produced, fixed-depth capillary fill chamber. The chamber used until 2002 was the Microcell MC-20-2 from Conception Technologies (San Diego, CA). This was replaced by the Leja Standard Count 20-micron analysis chamber (Leja Products, Nieuw Vennep, The Netherlands) during subsequent years. When the chamber was full the slide was placed in a heated stage at 37 C. The stage in turn was placed on the microscope and assessed using the Hamilton Thorne (Beverly, MA) HTM-S Semen Analyser until the year 2000, after which the Hamilton Thorne version 10 HTM- CEROS was used. A minimum of 200 sperm or two frames were counted. Local comparisons of changes in chamber and software were performed. These showed no significant difference to sperm densities or motilities. Progressive motility was determined as the proportion of sperm showing evidence of movement (WHO grades A and B) to the total number of spermatozoa counted (WHO grades A, B, C, and D) (9, 10). Sperm morphology was also analyzed according to WHO instructions. The National External Quality Assessment Service ( provided a means of external quality control for the laboratory, and quality checks were carried out four times per year in a central laboratory. No nonconformities were reported. Internal audits for adherence to standard operating procedures during sample preparation and analysis, as well as weekly comparisons between technicians, were additional internal quality control measures. Statistical Analysis Cases were couples who had spontaneous pregnancies, whereas controls included those with no recorded pregnancies. Data were analyzed using commercial software (SPSS 16; SPSS, Chicago, IL). Mean ages for both partners were compared using two-sample t-tests. Median values for other continuous and ordinal variables were compared with the Mann-Whitney test. Categoric variables were compared using the c 2 test. Statistical significance was defined as P<.05. Correlation between sperm parameters was tested using Spearman s rank correlation. Logistic regression was used to test for effects of semen parameters after adjusting for the confounding variables male and female age, parity, duration of infertility, and year of first visit. A receiver operating characteristic (ROC) curve was produced to examine the predictive value of sperm parameters in terms of pregnancy. RESULTS Of 5,077 couples residing in Aberdeen City District who attended the AFC between 1994 and 2003, we excluded couples with azoospermia or no semen analysis report (n ¼ 1,500), bilateral and unilateral fallopian tube blockage (n ¼ 867), anovulation (n ¼ 720), history of vasectomy (n ¼ 101) and female sterilization (n ¼ 20), and those who used donated gametes (n ¼ 2) (Fig. 1). From the remaining group, we also excluded couples who had treatment-related pregnancies (n ¼ 653). Records of 1,426 remaining couples who either had no pregnancies or spontaneous pregnancies only were linked with the AMND database to match for pregnancy records. Of these, 488 couples were confirmed to have a spontaneous conception within 180 weeks of first attending the fertility clinic, whereas 938 did not. Most variables studied were available for >95% of couples in both the spontaneously pregnant and nonpregnant groups. The exceptions to this were male body mass index (BMI), female BMI, percentage round cells, and period of abstinence, which were available for 43%, 65%, 74%, and 73% of couples, respectively. Demographic details for pregnant and nonpregnant couples are detailed in Table 1. The mean age of the women and men who did not achieve spontaneous conception was greater than that for those who did (P<.001) (Table 1). Median parity was significantly greater among women who became spontaneously pregnant (median ¼ 1) compared with women who did not (median ¼ 0) (P¼.048). Median duration of infertility was significantly greater in the nonpregnant couples (24 months) compared with the pregnant couples (18 months) (P<.001). There was a small but statistically significant association between male drinking and spontaneous pregnancy (P¼.032), with 91.8% of men drinking some alcohol among the couples with a spontaneous pregnancy and only 88.9% among those without. Male smoking, female smoking, female alcohol consumption, period of sexual abstinence before producing the semen sample, and male and female BMI were not significantly different between cases and controls. Male factor infertility was more common in couples who did not get pregnant (41.1%) compared with those who did (34.9%) (P¼.026). Unexplained factor was more common in the spontaneously pregnant group (57.1% vs. 37.6%; P<.001). The prevalence of endometriosis factor was not significantly different between the groups (P¼.172). The median sperm density was /ml for the pregnant group, compared with /ml in those with no pregnancy within 180 weeks (P¼.065). Median sperm motility was significantly greater in the spontaneously pregnant group (48% vs. 41%; P¼.002), as was normal sperm morphology (12% vs. 9%; P<.001). Sperm density, sperm morphology, and sperm motility were all positively correlated with each other (P<.001) in both the pregnant and nonpregnant couples. After adjusting for differences in male and female age, parity, year of first visit, and duration of infertility, sperm 626 Sripada et al. Semen parameters and spontaneous pregnancy Vol. 94, No. 2, July 2010

4 TABLE 1 Comparison of patients between spontaneously pregnant and nonpregnant groups. Variable Nonpregnant (n [ 938) Spontaneously pregnant (n [ 488) P value a Female age (y), mean (SD) 32.0 (5.4) 30.6 (4.8) <.001 Male age (y), mean (SD) 34.2 (6.1) 33.2 (5.4).001 Parity 0 (0 1) 1 (0 1).048 Duration of infertility (mo) 24 (17 36) 18 (14 24) <.001 Male smoking.767 Nonsmokers (0) 633 (69.9) 341 (71.5) Moderate (1 19) 236 (26.1) 120 (25.2) Heavy (R20) 36 (4.0) 16 (3.4) Male alcohol.032 Nondrinkers 101 (11.1) 39 (8.2) <20 U/wk 795 (87.7) 425 (89.1) >20 U/wk 11 (1.2) 13 (2.7) Female smoking.327 Nonsmokers (0) 719 (77.9) 367 (75.8) Moderate (1 19) 193 (20.9) 114 (23.6) Heavy (R20) 11 (1.2) 3 (0.6) Female alcohol.234 Nondrinkers 156 (16.9) 73 (15.1) <20 U/wk 763 (82.7) 410 (84.9) >20 U/wk 4 (0.4) 0 Male BMI (kg/m 2 ) 25.5 ( ) 25.7 ( ).914 Female BMI (kg/m 2 ) 23.6 ( ) 23.4 ( ).119 Sperm factor infertility 370 (41.1) 167 (34.9).026 Unexplained infertility 339 (37.6) 273 (57.1) <.001 Endometriosis 49 (5.4) 18 (3.8).172 Sperm density (10 6 /ml) 51 (27 85) 54 (32 86).065 Sperm progressive 41 (22 57) 48 (33 61).002 motility (%) Sperm normal 9 (5 18) 12 (6 20) <.001 morphology (%) Round cells (%) 0.1 ( ) 0.0 ( ).280 Period of abstinence (d) 4 (4 6) 4 (4 6).486 Note: Values are number (percentage) or median (interquartile range), unless otherwise noted. a Chi-square tests for categoric variables, t-test for age, Mann-Whitney test for other continuous or ordinal variables. Sripada. Semen parameters and spontaneous pregnancy. Fertil Steril motility and percentage of normal sperm morphology were still significantly associated with spontaneous pregnancy (P¼.007 and P¼.002, respectively). Including both of these together did not significantly improve the fit of the model. Sperm density was not a significant predictor of pregnancy, even after adjusting for possible confounders (P¼.226). Although statistically significant, both sperm motility and morphology had only moderate predictive value for spontaneous pregnancy. For motility the area under the ROC curve was (95% confidence interval ; P¼.006). For morphology the area under the ROC curve was (95% confidence interval ; P<0.001) (Fig. 2). DISCUSSION Our study showed a significant difference in sperm morphology and motility between subfertile couples who achieved spontaneous pregnancy and those who did not. Our data are based on a large sample of consecutive couples attending the only fertility clinic in the defined geographic region. Diagnostic criteria in the AFC have remained unchanged over time, and couples were investigated by standard protocol. The presence of a single andrology laboratory and single specialized fertility clinic in the Grampian Region of Scotland implies that the data are genuinely population based. Fertility and Sterility â 627

5 FIGURE 2 Receiver operating characteristic curve for prediction of spontaneous pregnancy using sperm motility (short dashes) or sperm percentage normal morphology (long dashes). Sripada. Semen parameters and spontaneous pregnancy. Fertil Steril One of the potential problems associated with this study is the fact that pregnancy outcomes are only available for women residing in Aberdeen City District who deliver in Aberdeen. Details of women who have moved away after attending the fertility clinic and delivered elsewhere in the country are not recorded in the AMND. However, the documented low emigration rate of approximately 3% in this part of the world ensures that these women constitute a small minority (11, 12). Our study is limited by the inclusion of couples referred to the infertility clinic, as opposed to a general population. However, the population has been prospectively followed up to spontaneous conception. Unlike in studies involving couples who have come off contraception or who were recruited from antenatal classes (1, 11, 12), we were able to exclude causes of subfertility like fallopian tube blockage as couples were investigated because of referral to the clinic. Some male pathologies, such as varicocele and other testicular abnormalities, were not adjusted for in the analysis because the effects of these parameters would result in alterations in semen parameters. Because practice can change over time, we have adjusted for the data for the year in which the semen sample was produced. Couples with higher proportions of sperm with normal morphology or progressive motility were more likely to conceive spontaneously, but we were unable to identify a clear cut-off value to discriminate between this group and those who did not conceive spontaneously. Although sperm concentration is also important (2, 13 15), we did not see a correlation between this and successful outcome in our study. Recognized factors like female age, duration of infertility, and parity were significantly different between the pregnant and nonpregnant groups. After accounting for these factors in a binary logistic regression model, differences in normal sperm morphology and progressive sperm motility continued to be significantly different between the two groups. Sperm motility had a significant association with spontaneous pregnancy but lower predictive power than sperm morphology. Similar results were obtained in the past when a comparison was made between manual and computer-assisted sperm assessments, favoring the automated assessment (16), including mean head area of sperm. The current revised threshold of 15% for sperm morphology is based on data from IVF studies. In a 1998 review by Coetzee (5), a threshold for sperm morphology of 5% was reached in IVF programs because there was a significant difference in the pregnancy rate below this level. There is a need for more data in the threshold estimation in the in vivo situation. Four such studies have described the threshold for sperm morphology to vary between 4% and 10% (1, 4, 17, 18). Although Ombelet et al. (19) went on to include the sperm concentration retrieved after swim-up as an additional prognostic variable, many studies (20 22) showed the association with sperm morphology independent of any other semen parameter. Data from Guzick et al. (4) reveal a fertile threshold for sperm morphology of >12% in a large, randomized, controlled trial (n ¼ 1,460) involving a subfertile male population vs. fertile men recruited from prenatal classes. In this study, sperm morphology was the best discriminator for predicting fertility. Bonde et al. (2) showed that a higher proportion of normal sperm morphology increased the likelihood of pregnancy independent of sperm concentration. A study from Singapore on 243 men of proven fertility (wives pregnant at the time of semen analysis) had found a median sperm morphology of 19% (range, 15% 35%). Slama et al. (13) have studied the association of sperm parameters and time to pregnancy in four cities, and they found that sperm concentration less than /ml was associated with decreased fecundity and sperm concentration up to /ml and morphology up to 39% influenced the time to pregnancy in the same direction in each of the cities independent of season (13). In our study using ROC curves, the best threshold reached for sperm morphology affecting spontaneous conception was approximately 9.5%, with a sensitivity of 62% and a specificity of 52%. This is in keeping with the data from Ombelet et al. (19), from data on 430 first-pregnancy planners. However, a recent study by Nallella et al. (23) did not find morphology of prognostic value, and they faced considerable overlap in semen parameters among donors (n ¼ 91), prospective fathers (n ¼ 56), and men with male factor infertility (n ¼ 166) whose female spouse had normal fertility investigation results. Gunalp et al. (17) found that progressive motility proved to be a somewhat better predictor of subfertility than sperm morphology, with area under the curve values of 70.7% and 69.7%, respectively. In the study by Montanaro Gauci et al. 628 Sripada et al. Semen parameters and spontaneous pregnancy Vol. 94, No. 2, July 2010

6 (24), sperm motility was a significant predictor of IUI outcome, with the pregnancy rate almost three times higher when sperm motility exceeded 50%. This was confirmed by other studies (25, 26). Although the value of standard sperm parameters has been repeatedly questioned, a review of the literature between 1983 and 2002 revealed that they were found to have reasonable predictive power independent of each other, and their clinical value increased when these were considered in combination (27). The review recommended that the lowest cut-off values described below should be used to identify subfertile men in the general population. In keeping with IVF and IUI data, normal sperm morphology of <4% indicated a higher risk of nonpregnancy. The thresholds for sperm concentration and motility were less clear, and a concentration of < / ml and sperm motility of <30% agreed with data from four of the studies included in the review (1, 4, 17, 18). Previous externally validated prediction models of spontaneous pregnancy using female, male, and couple factors have excluded men with very poor sperm parameters. Earlier publications have used cut-off values for total motile count of > /ml (28) and > /ml (29). Independent values for area under the curve for the semen parameters were not described in these articles. Sperm morphology has been shown to be associated with sperm function tests in some studies (21, 30) but not others (31). Different methods and criteria for evaluation for sperm morphology are used worldwide. However, regardless of the precise method used, abnormal sperm morphology has been shown to be related to delayed fertilization and abnormal embryo quality (32 34) in IVF. Recent studies have linked abnormal sperm morphology to sperm DNA abnormalities (35). Bungum et al. (36) have shown that the DNA fragmentation index can be an independent predictor of fertility in couples undergoing IUI and that when the DNA fragmentation index exceeds 30%, ICSI should be the preferred treatment; this is confirmed in a recent systematic review (37). Given the lack of rigorous laboratory methodology for standardization and wide variations in sperm parameters within populations, there are limitations in using these as prognostic indices. However, it has been argued that sperm morphology, when assessed carefully using strict Tygerberg criteria, can be useful in clinical settings (36). Although manual morphology assessment has been subject to criticism, automated morphology assessments, although reproducible, are as yet of unproven value. The possible errors that can arise during slide preparation and staining can apply to both techniques. To date there is no reliable test that detects the competent capacitated sperm that is capable of fertilizing the egg. 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